ML Anthology

Connect Multi-Agent Path Finding: Generation and Visualization

Arthur Queffelec, Ocan Sankur, François Schwarzentruber
IJCAI 2021 pp. 5008-5011
doi:10.24963/IJCAI.2021/714 /ijcai/2021/queffelec2021ijcai-connect/

Abstract

We present a generic tool to visualize missions of the Connected Multi-Agent Path Finding (CMAPF) problem. This problem is a variant of MAPF which requires a group of agents to navigate from an initial configuration to a goal configuration while maintaining connection. The user can create an instance of CMAPF and can play the generated plan. Any algorithm for CMAPF can be plugged into the tool.

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Cite

Text

Queffelec et al. "Connect Multi-Agent Path Finding: Generation and Visualization." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/714

Markdown

[Queffelec et al. "Connect Multi-Agent Path Finding: Generation and Visualization." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/queffelec2021ijcai-connect/) doi:10.24963/IJCAI.2021/714

BibTeX

@inproceedings{queffelec2021ijcai-connect,
  title     = {{Connect Multi-Agent Path Finding: Generation and Visualization}},
  author    = {Queffelec, Arthur and Sankur, Ocan and Schwarzentruber, François},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {5008-5011},
  doi       = {10.24963/IJCAI.2021/714},
  url       = {https://mlanthology.org/ijcai/2021/queffelec2021ijcai-connect/}
}